C10692: A Method for Automatically Evaluating Skill for Motion TrainingNovelty:
A hardware and software system designed to track and to automatically grade and annotate the motions of a specific user operating one or more surgical devices.
Value Proposition:
Surgeon skill level has been demonstrated to directly affect patient outcomes; however, there are few tools available to objectively assess clinical technical skills required for operation of teleoperated robotic surgical systems, which are increasingly used in clinical surgical procedures. This invention accesses and uses operator performance data recorded from robotic surgical systems to provide objective quantification of skill level of a specific user both at the individual skill level and in the entirety of surgical skills. Unique advantages of this system and method of clinical technical skill assessment include:
• Reliable, quantitative, and objective assessment of users of all technical proficiencies in a variety of surgical procedures
• Real-time or offline feedback of annotated motions and video with skill classification using augmented reality
• Identification and comparison of skilled and unskilled operators motion characteristics to quantify task proficiency, distinguish skill level, and compare individuals with an expert
• Effective training of users without the need for a surgeon supervisor
Technical Details:
Johns Hopkins researchers have developed an effective system and method of quantifying clinical surgical skills. Data is collected from user interaction with a surgical robotic system during user performance of a specific surgical skill. This data is in the form of video recorded user motion characteristics. Assessed skills are segmented into one or more skill components, each of which has specific motion characteristics. Evaluation of user performance is completed by comparing quantitative variables of user motion characteristics (time per task, idle motion time, sequence of motions, timing of motions) in each skill component to previously collected data for similar surgical tasks. The system quantifies this comparison to provide the user with an overall categorization of skills into one of three experience levels: expert, intermediate, or novice. In addition, this system allows for additional, data-driven teaching to guide novices through previously recorded expert motions.
Looking for Partners:
To develop and commercialize the technology as a training system that can be combined for use with new or existing surgical robotic systems.
Stage of Development:
Prototype demonstration in a relevant environment (field testing).
Data Availability:
Prototype
Publications/Associated Cases:
Med Image Comput Comput Assist Interv. 2009;12(Pt 1):435-42.
MICCAI M2Cai workshop, 2009
Med Image Comput Comput Assist Interv. 2009;12(Pt 1):426-34.
